Code accompanying the paper "Diverse projection ensembles for distributional reinforcement learning"

DOI:10.4121/6b996f9c-27a9-4332-a0b6-d186ac6c4467.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/6b996f9c-27a9-4332-a0b6-d186ac6c4467

Datacite citation style

Zanger, Moritz A.; Boehmer, Wendelin; Spaan, M.T.J. (Matthijs) (2025): Code accompanying the paper "Diverse projection ensembles for distributional reinforcement learning". Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/6b996f9c-27a9-4332-a0b6-d186ac6c4467.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Software

This is the official code repository of projection-ensemble DQN, accompanying the paper "Diverse projection ensembles for distributional reinforcement learning" (ICLR 2024).

History

  • 2025-08-15 first online, published, posted

Publisher

4TU.ResearchData

Format

.py

Funding

  • Epistemic AI (grant code 964505) [more info...] EXCELLENT SCIENCE - Future and Emerging Technologies (FET) (EU Horizons 2020)

Organizations

Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems, Sequential Decision Making Group

To access the source code, use the following command:

git clone https://data.4tu.nl/v3/datasets/26e6f861-05e8-4446-b58b-4c045bf8b60c.git "diverse-projection-ensembles"

Or download the latest commit as a ZIP.